Using the Global Ensemble Forecast System (GEFS) Reanalysis to Map Pathways of Sand Transport in the Rub' al Khali

Authors: Kevin Mulligan*, Texas Tech University, Fahad A. Almutlaq, King Saud University
Topics: Geomorphology, Earth Science, Climatology and Meteorology
Keywords: aeolian, sand dunes, Rub' al Khali
Session Type: Poster
Day: 4/5/2019
Start / End Time: 8:00 AM / 9:40 AM
Room: Lincoln 2, Marriott, Exhibition Level
Presentation File: Download

In most remote desert regions of the world there are only a few weather stations, often located hundreds of kilometers apart. In this situation, it is difficult to analyze the wind data in any meaningful way to understand the relationship between wind regime, sand transport and dune morphology. To address this problem, this study used the Global Ensemble Forecast System (GEFS) Reforecast to understand the nature of aeolian processes in the Rub’ al Khali, the largest and perhaps most significant sand sea in the world. The GEFS Reforecast is a raster dataset that includes the historical near-surface (~10 m) wind at a spatial resolution of 0.5° (~50 km). In essence, each grid cell in the dataset represents a virtual weather station within the sand sea. Using the GEFS Reanalysis dataset, the drift potential (DP) and resultant drift potential (RDP) were calculated for each or the 204 grid cells covering the Rub’ al Khali. The results from this study show that the long-term resultant drift potential varies in magnitude and direction across the dune field, defining pathways of potential sand transport. In general, sand transport trends from the north-east toward the south-west. Moreover, the analysis of the RDP/DP ratio shows that the directional variability in sand movement varies greatly in different parts the sand sea. Taken together, the resultant potential drift (RDP) and directional variability in sand movement (RDP/DP) can be used to explain the varied dune morphology within the Rub’ al Khali.

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